As long as Artificial Intelligence is pervading all aspects of our lives, it is becoming instrumental also for crucial aspects, impacting directly our existence and well-being. This means that some of its decisions must be checked and validated, which in turn requires them to be explainable. The explainable-by-design approach in Artificial Intelligence is the symbolic one, based on formal logics. It applies human-like automated reasoning and relies on suitable knowledge representations. The most widely known and adopted knowledge representation approach nowadays comes from the Semantic Web community, but due to its peculiarities it has some limitations and shortcomings. In this paper we propose an alternate framework that significantly expands the range of applicable automated reasoning strategies.
The GraphBRAIN Knowledge Graph Framework for XAI through Multistrategy Reasoning
Ferilli S.;Bernasconi E.;Redavid D.
2026-01-01
Abstract
As long as Artificial Intelligence is pervading all aspects of our lives, it is becoming instrumental also for crucial aspects, impacting directly our existence and well-being. This means that some of its decisions must be checked and validated, which in turn requires them to be explainable. The explainable-by-design approach in Artificial Intelligence is the symbolic one, based on formal logics. It applies human-like automated reasoning and relies on suitable knowledge representations. The most widely known and adopted knowledge representation approach nowadays comes from the Semantic Web community, but due to its peculiarities it has some limitations and shortcomings. In this paper we propose an alternate framework that significantly expands the range of applicable automated reasoning strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


